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| ID | Type | Description | Link |
|---|---|---|---|
| 09128006 | Other Grant/Funding Number | U.S. Department of Defense (TATRC) |
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Amputees often choose not to wear prostheses due to marginal performance or may settle for a prosthesis that offers only cosmetic improvement, but lacks function. A simulation tool consisting of a robotics-based human body model (RHBM) to predict functional motions, and integrated modules for aid in prescription, training, comparative study, and determination of design parameters of upper extremity prostheses will be developed.
The main objective of collecting and analyzing human movement during several common tasks is to optimize and validate the robotics based human model. The range of motion data of subjects performing activities of daily living such as opening a door, turning a wheel, grooming, eating, bilateral lifting, as well as recreational and sport activities such as swinging a baseball bat, and golf club will be analyzed. This motion analysis data will also be used to compare data between four groups: a control group (n=10), a braced group simulating prosthesis use (n=10), a group wearing a transradial prosthesis (n=10) and a group wearing a transhumeral prosthesis (n =10).
Data will be collected by an 8 camera Vicon© motion analysis system during one 3-4 hour testing period. Forty-five reflective markers will be attached to subjects skin and clothing via a double sided adhesive electrode collar. The cameras work on an infrared spectrum and the markers are passive reflective spheres. Relations between marker positions and anatomical / known positions on the body are used to calculate the positions of body segments.This analysis will provide information on movement strategies, compensatory motion, and socket movement associated with the selected tasks for transradial and transhumeral prostheses. Differences in the range of motion of the prostheses users and control subjects will be calculated to determine compensatory motion. The movement of the prosthesis's socket as a function of task and other factors will also be measured. Measured data will be used to minimize error in the simulation of the upper body movement. Knowledge of human motor function given in the recorded data can be extended to give insight to movement parameters when designing new prosthetics. Simulations will be optimized to the collected data using a regressive best fit method.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Amputees | upper limb amputees | ||
| Non-amputees | No longer recruiting non-amputees |
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| Measure | Description | Time Frame |
|---|---|---|
| Shoulder angle | The shoulder angle (rotation, flexion/extension and abduction/adduction) will be measured during several tasks during one 3-4 hour testing period. | During task completion |
| Elbow angle | The elbow angle ( flexion/extension and forearm pronation/supination) will be measured during several tasks during one 3-4 hour testing period. | During task completion |
| Wrist angle | The wrist angle (flexion/extension and abduction/adduction) will be measured during several tasks during one 3-4 hour testing period. | During task completion |
| Torso angle | The torso angle (rotation, forward/backward bending and right/left sideways bending) will be measured during several tasks during one 3-4 hour testing period. | During task completion |
| Measure | Description | Time Frame |
|---|---|---|
| Validation of robotics based human body model | The robotics based human body model will be validated by comparing the joints (shoulder, elbow, wrist, torso) angles collected from the motion analysis system while participants are completing activities of daily living with the joint angles predicted by the model. The two data sets will be compared using a root mean error calculation. | After motion data analysis |
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Inclusion Criteria:
Exclusion Criteria:
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Two groups will be studied: non-amputees and upper limb amputees. The subjects will be recruited from around the community.
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| Name | Affiliation | Role |
|---|---|---|
| Rajiv Dubey, PhD | University of South Florida | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of South Floria RRT building | Tampa | Florida | 33612 | United States |
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| Label | URL |
|---|---|
| Center for Rehabilitation, Robotics and Assistive Technologies | View source |
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